at the intersection of neuroscience and AI.

Menu

Why Tononi is wrong

In a recent NY Times article, Tononi chooses to propose a rather sketchily-described “Shannon informational” model to supplant a gamma synchrony model partly on these grounds;

“Dr. Tononi sees serious problems in these models. When people lose consciousness from epileptic seizures, for instance, their brain waves become more synchronized. If synchronization were the key to consciousness, you would expect the seizures to make people hyperconscious instead of unconscious, he said. “

Jouny et al (2010) http://www.ncbi.nlm.nih.gov/pubmed/19910249 surely should have suggested that this is premature closure, with an INCREASE in signal complexity – that is, decline in synchrony – associated with seizure

Our study of ECOG data (electrodes directly attached to the cortex, not on the scalp) confirms this. Sleep signal is least complex/disordered under PCA, first component explains 97%, awake is next, with 93% explained by the first component, while seizure has just 63% explained by first component.

“Jouny et al (2010) http://www.ncbi.nlm.nih.gov/pubmed/19910249 surely should have suggested that this is premature closure, with an INCREASE in signal complexity – that is, decline in synchrony – associated with seizure”

So what’s wrong with Tononi theory then?
Seizures are not always make someone unconscious, and sometimes even accompanied by hallucinations – in such cases, increase in complexity should be expected (accordingly to the Tononi theory) and this paper provides additional evidence in support of the theory :p